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Scenarios of the organic food market in Europe

Author

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  • Zanoli, Raffaele
  • Gambelli, Danilo
  • Vairo, Daniela

Abstract

Scenario analysis is a qualitative tool for strategic policy analysis that enables researchers and policymakers to support decision making, and a systemic analysis of the main determinants of a business or sector. In this study, a scenario analysis is developed regarding the future development of the market of organic food products in Europe. The scenario follows a participatory approach, exploiting potential interactions among the relevant driving forces, as selected by experts. Network analysis is used to identify the roles of driving forces in the different scenarios, and the results are discussed in comparison with the main findings from existing scenarios on the future development of the organic sector.

Suggested Citation

  • Zanoli, Raffaele & Gambelli, Danilo & Vairo, Daniela, 2012. "Scenarios of the organic food market in Europe," Food Policy, Elsevier, vol. 37(1), pages 41-57.
    • Handle: RePEc:eee:jfpoli:v:37:y:2012:i:1:p:41-57
    DOI: 10.1016/j.foodpol.2011.10.003
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    References listed on IDEAS

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    1. Vairo, Daniela & Haring, Anna Maria & Dabbert, Stephan & Zanoli, Raffaele, 2006. "Policies supporting organic food and farming in the EU: assessment and development by stakeholders in 11 European countries," 98th Seminar, June 29-July 2, 2006, Chania, Crete, Greece 10109, European Association of Agricultural Economists.
    2. Makridakis, Spyros & Taleb, Nassim, 2009. "Decision making and planning under low levels of predictability," International Journal of Forecasting, Elsevier, vol. 25(4), pages 716-733, October.
    3. Makridakis, Spyros & Chatfield, Chris & Hibon, Michele & Lawrence, Michael & Mills, Terence & Ord, Keith & Simmons, LeRoy F., 1993. "The M2-competition: A real-time judgmentally based forecasting study," International Journal of Forecasting, Elsevier, vol. 9(1), pages 5-22, April.
    4. Sniezek, Janet A., 1989. "An examination of group process in judgmental forecasting," International Journal of Forecasting, Elsevier, vol. 5(2), pages 171-178.
    5. Makridakis, Spyros & Taleb, Nassim, 2009. "Living in a world of low levels of predictability," International Journal of Forecasting, Elsevier, vol. 25(4), pages 840-844, October.
    6. Wright, George & Goodwin, Paul, 2009. "Decision making and planning under low levels of predictability: Enhancing the scenario method," International Journal of Forecasting, Elsevier, vol. 25(4), pages 813-825, October.
    7. Ang, Soon & O'Connor, Marcus, 1991. "The effect of group interaction processes on performance in time series extrapolation," International Journal of Forecasting, Elsevier, vol. 7(2), pages 141-149, August.
    8. Bunn, Derek W. & Salo, Ahti A., 1993. "Forecasting with scenarios," European Journal of Operational Research, Elsevier, vol. 68(3), pages 291-303, August.
    9. Makridakis, Spyros & Hibon, Michele, 2000. "The M3-Competition: results, conclusions and implications," International Journal of Forecasting, Elsevier, vol. 16(4), pages 451-476.
    10. Orrell, David & McSharry, Patrick, 2009. "System economics: Overcoming the pitfalls of forecasting models via a multidisciplinary approach," International Journal of Forecasting, Elsevier, vol. 25(4), pages 734-743, October.
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    Cited by:

    1. Gambelli, Danilo & Alberti, Francesca & Solfanelli, Francesco & Vairo, Daniela & Zanoli, Raffaele, 2017. "Third generation algae biofuels in Italy by 2030: A scenario analysis using Bayesian networks," Energy Policy, Elsevier, vol. 103(C), pages 165-178.
    2. Yawson, Robert M. & Greiman, Bradley C., 2017. "Strategic flexibility analysis of agrifood nanotechnology skill needs identification," Technological Forecasting and Social Change, Elsevier, vol. 118(C), pages 184-194.
    3. Narcis-Alexandru Bozga, 2015. "Consumers Behavior Features Upon the Organic Products in Romania," International Conference on Marketing and Business Development Journal, The Bucharest University of Economic Studies, vol. 1(1), pages 209-217, July.
    4. Sisto, Roberta & Lopolito, Antonio & van Vliet, Mathijs, 2018. "Stakeholder participation in planning rural development strategies: Using backcasting to support Local Action Groups in complying with CLLD requirements," Land Use Policy, Elsevier, vol. 70(C), pages 442-450.
    5. Olga M. Moreno-Pérez & Amparo Blázquez-Soriano, 2023. "What future for organic farming? Foresight for a smallholder Mediterranean agricultural system," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 11(1), pages 1-24, December.

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